Method for improving unit load splicing capacity

Abstract

The invention provides a method for improving unit load splicing capacity, and relates to the technical field of power system load optimization, and the method comprises the steps: determining a calculation boundary condition of a power grid system in a preset region and an operation mode of a power plant unit based on the information of the power grid system; dividing the power plant units into fast adjusting units and slow adjusting units based on the adjusting time of the power plant units; dividing output gears of the power plant units based on the unit capacities of the rapid adjustment unit and the slow adjustment unit; based on the predetermined health state level of the power plant unit, optimizing the output gear of the power plant unit; in each operation mode, stability checking is carried out based on the output gear of the power plant unit; constructing an optimization model taking active power maximization of the load station as a target function; introducing stability check as a constraint condition of the optimization model; the optimization model is solved through an optimization algorithm, the maximum value of the power plant unit load connection is obtained, and the unit load connection capacity can be fully exerted after the large-capacity thermal power unit is put into operation.

Description

Technical Field

[0001] The present invention relates to the technical field of power system load optimization, and particularly to a method for improving the load carrying capacity of a unit. Background Art

[0002] In areas with rapid load growth, especially in areas with high-energy-consuming continuous industrial loads, large-capacity thermal power units are usually put into operation or expanded. However, in the planning and design of the power grid, factors such as the output of the unit and the short-circuit capacity are often not comprehensively considered, which may lead to a decrease in the transient stability level of the power grid system after the unit is put into operation, and then the problem of the unit's load carrying capacity decreasing, unable to meet the actual needs. Summary of the Invention

[0003] The present invention provides a method for improving the load carrying capacity of a unit to solve the technical problem that the load carrying capacity of the unit cannot be fully exerted after putting into operation or expanding a large-capacity thermal power unit in the prior art.

[0004] On the one hand, the present invention provides a method for improving the load carrying capacity of a unit, including:

[0005] Based on the power grid system information, determining the calculation boundary conditions of the power grid system and the operation mode of the power plant unit in a preset area;

[0006] Based on the regulation time of the power plant unit, dividing the power plant unit into a fast-regulation unit and a slow-regulation unit;

[0007] Based on the unit capacities of the fast-regulation unit and the slow-regulation unit, dividing the output levels of the power plant unit;

[0008] Based on the pre-determined health status level of the power plant unit, optimizing the output levels of the power plant unit;

[0009] Under each of the operation modes, performing stability check based on the output levels of the power plant unit;

[0010] Constructing an optimization model with the maximum active power of the load station as the objective function;

[0011] Introducing the stability check as a constraint condition of the optimization model;

[0012] Solving the optimization model through an optimization algorithm to obtain the maximum value of the load carried by the power plant unit.

[0013] According to the method for improving the load carrying capacity of a unit provided by the present invention, the performing stability check based on the output levels of the power plant unit includes:

[0014] When the power plant unit is at each output level, perform thermal stability checking, transient voltage stability checking, and transient power angle stability checking; among them,

[0015] The thermal stability checking includes:

[0016] Under normal and fault conditions, after a newly commissioned power plant unit or an additional load, detect whether the active power transmitted by each substation and line belongs to its respective preset power range;

[0017] The transient voltage stability checking includes:

[0018] Judge whether the reduction amplitude of the load bus voltage after a fault meets the preset transient voltage stability constraint; among them, the preset transient voltage stability constraint is that the load bus voltage can recover above the preset threshold within a preset time;

[0019] The transient power angle stability checking includes:

[0020] Judge whether the maximum power angle difference during the power angle swing of each power plant unit in the network is less than or equal to the preset angle, and whether the power angle swing of each power plant unit shows a decaying oscillation trend and finally stabilizes within the preset interval range.

[0021] According to a method for improving the load carrying capacity of a unit provided by the present invention, the calculation boundary conditions include the maximum operating capacity of a substation, the load power factor, and the bus voltage, and the operating modes include the unit startup combination mode of a power plant unit and the maintenance mode of a power grid system;

[0022] Among them, the maximum operating capacity of the substation is determined by the following method:

[0023] Based on the rated capacity and historical operating capacity data of substations in a preset area, obtain the maximum operating capacity of the substation;

[0024] The load power factor is determined by the following method:

[0025] Analyze the change law of the load power factor in a preset area to determine the value range of the load power factor;

[0026] The bus voltage is determined by the following method:

[0027] Based on the operating voltage curve of the bus, extract the voltage fluctuation range in historical data, and combine the lower limit value of the operating voltage curve with the lowest point of the voltage fluctuation to determine the bus voltage;

[0028] The unit startup combination mode includes all power plant units starting up simultaneously and some power plant units starting up simultaneously;

[0029] The maintenance method includes the single-outage maintenance method for adjacent lines, units, and transformers.

[0030] According to a method for improving the load-carrying capacity of a unit provided by the present invention, dividing the output levels of the power plant units based on the unit capacities of the fast-adjusting units and the slow-adjusting units includes:

[0031] For the fast-adjusting units, when the unit capacity of the power plant unit is less than the first capacity threshold, set the output level according to the first rated output ratio; when the unit capacity of the power plant unit is greater than the first capacity threshold, set the output level according to the second rated output ratio;

[0032] For the slow-adjusting units, when the unit capacity of the power plant unit is less than the first capacity threshold, set the output level according to the second rated output ratio; when the unit capacity of the power plant unit is greater than the first capacity threshold, set the output level according to the third rated output ratio;

[0033] Wherein, the first rated output ratio is less than the second rated output ratio is less than the third rated output ratio.

[0034] According to a method for improving the load-carrying capacity of a unit provided by the present invention, optimizing the output levels of the power plant units based on the pre-determined health status levels of the power plant units includes:

[0035] When the health status level of the power plant unit is lower than the preset health threshold, reduce the rated output ratio of the output level of the power plant unit;

[0036] When the health status level of the power plant unit is higher than the preset health threshold, increase the rated output ratio of the output level of the power plant unit.

[0037] According to a method for improving the load-carrying capacity of a unit provided by the present invention, the determined health status level of the power plant unit includes:

[0038] Collect the operation data of the power plant unit within a preset time period; wherein, the operation data includes the number of starts, the number of stops, the number of faults, and the maintenance records;

[0039] Based on the operation data, calculate the health status level of the power plant unit using a preset health assessment model.

[0040] According to a method for improving the load-carrying capacity of a unit provided by the present invention, calculating the health status level of the power plant unit using a preset health assessment model based on the operation data includes:

[0041] Perform normalization processing on the operation data;

[0042] Based on statistical analysis methods, establish the correlation between each operating data and the unit health status;

[0043] Based on the correlation, determine the health scores of each operating data;

[0044] Based on the health scores of each operating data, obtain the health status level of the power plant unit.

[0045] According to a method for improving the unit load carrying capacity provided by the present invention, the establishing the correlation between each operating data and the unit health status based on statistical analysis methods includes:

[0046] Collect historical unit operating data and its corresponding health status level as sample data;

[0047] Adopt statistical analysis methods such as Pearson correlation coefficient or Spearman rank correlation coefficient to calculate the correlation between each operating data and the unit health status level;

[0048] According to the correlation results, determine the influence weight of each operating data on the unit health status.

[0049] According to a method for improving the unit load carrying capacity provided by the present invention, the determining the health scores of each operating data based on the correlation includes:

[0050] According to the influence weight of each operating data on the unit health status, perform weighted summation on the normalized operating data to obtain the health scores of each operating data. The formula is as follows:

[0051] Among them, S is the health score of all operating data, w i is the influence weight of the i-th type of operating data, x i is the i-th type of normalized operating data, and n is the number of types of operating data.

[0052] According to a method for improving the unit load carrying capacity provided by the present invention, the obtaining the health status level of the power plant unit based on the health scores of each operating data includes:

[0053] Based on weighted average or non-linear combination function, calculate the health scores of each operating data to obtain the comprehensive health score of the unit;

[0054] According to the preset health status level division standard, map the comprehensive health score to the corresponding health status level.

[0055] The method for improving the unit load carrying capacity provided by the present invention can calculate the load carrying capacity of the unit more accurately by comprehensively considering various constraint conditions of the power grid system. It can maximize the load carrying capacity of the unit on the premise of ensuring the safe and stable operation of the power grid, which helps to better meet the load growth demand, especially in areas with rapid load growth. Through stability checks (such as transient voltage stability, transient power angle stability, etc.), it is ensured that the power grid can maintain stable operation under various operating modes and fault conditions. Improve the power grid's ability to respond to sudden faults and reduce the power outage risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0057] Figure 1 is a schematic flowchart of the method for improving the unit load carrying capacity provided by the embodiment of the present invention;

[0058] Figure 2 is a schematic diagram of the power grid structure in a region provided by the embodiment of the present invention;

[0059] Figure 3 is a load change trend diagram of starting three units in HY Power Plant provided by the embodiment of the present invention;

[0060] Figure 4 is a load change trend diagram of starting two units in HY Power Plant provided by the embodiment of the present invention;

[0061] Figure 5 is a schematic diagram of the structure of the system for improving the unit load carrying capacity provided by the embodiment of the present invention;

[0062] Figure 6 is a schematic diagram of the structure of the electronic device provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0064] Figure 1It is a schematic flowchart of a method for improving the unit load acceptance capacity provided by an embodiment of the present invention. The execution subject of this method can be a computer, a tablet computer, etc.

[0065] Refer to Figure 1 , the method for improving the unit load acceptance capacity may include the following steps.

[0066] Step 101: Based on the power grid system information, determine the calculation boundary conditions of the power grid system in the preset area and the operation mode of the power plant units.

[0067] In this step, the calculation boundary conditions may include at least one of the maximum operating capacity of the substation, the load power factor, and the bus voltage, and the operation mode may include the unit startup combination mode of the power plant and the maintenance mode of the power grid system.

[0068] Among them, the maximum operating capacity of the substation is determined by the following method:

[0069] Based on the rated capacity and historical operating capacity data of the substations in the preset area, obtain the maximum operating capacity of the substations. For example, find the maximum value in the historical operating capacity data, compare the maximum value with the rated capacity, and select the larger of the two as the maximum operating capacity. Or, when the maximum value of the historical operating capacity data is less than the rated capacity, take this maximum value as the maximum operating capacity, and when the maximum value of the historical operating capacity data is greater than the rated capacity, take the rated capacity as the maximum operating capacity.

[0070] The load power factor is determined by the following method:

[0071] Analyze the change law of the load power factor in the preset area to determine the value range of the load power factor. The change law refers to the dynamic change trend of the load power factor in terms of time (such as seasons, months), space (such as different regions, different load densities), or load characteristics (such as load types, load change rates). Generally, the value range of the load power factor is determined to be 0.9 - 0.95. 0.9 or 0.95 can be selected.

[0072] The bus voltage is determined by the following method:

[0073] Based on the operating voltage curve of the bus, extract the voltage fluctuation range in the historical data, and combine the lower limit value of the operating voltage curve with the lowest point of the voltage fluctuation to determine the bus voltage. For example, the minimum value of the lower limit value of the operating voltage curve and the lowest point of the voltage fluctuation can be used as the bus voltage, or the average value of the two can be used as the bus voltage.

[0074] The unit startup combination mode includes all power plant units starting up simultaneously and some power plant units starting up simultaneously.

[0075] The maintenance methods include the single-withdrawal maintenance methods for adjacent lines, units, and transformers. Single withdrawal can be understood as withdrawing one by one, that is, withdrawing one of them each time. When the next one needs to be withdrawn, the currently withdrawn one can be put into operation.

[0076] In this step, by determining the maximum operating capacity based on the rated capacity and historical operating capacity data of the substation, analyzing the variation law of the load power factor to determine its value range, combining the operating voltage curve and historical voltage fluctuations to determine the bus voltage, etc., and clarifying the unit startup combination method and maintenance method, accurate boundary conditions and operating modes are provided for the subsequent output level division and stability check, enhancing the operability and adaptability of the method.

[0077] Step 102: Divide the power plant units into fast-adjusting units and slow-adjusting units based on the adjustment time of the power plant units.

[0078] In this step, generally, a time threshold can be set. The units that can adjust their output within the time threshold are used as fast-adjusting units, and the units that cannot adjust their output within the time threshold are used as slow-adjusting units. For example, fast-adjusting units may include gas turbines, pumped-storage units, etc., and slow-adjusting units may include old thermal power plants, large hydropower plants, etc. with slower adjustment speeds.

[0079] Step 103: Divide the output levels of the power plant units based on the unit capacities of the fast-adjusting units and slow-adjusting units.

[0080] In this step, dividing the output levels of the power plant units based on the unit capacities of the fast-adjusting units and slow-adjusting units may include:

[0081] For fast-adjusting units, when the unit capacity of the power plant unit is less than the first capacity threshold, set the output level according to the first rated output ratio; when the unit capacity of the power plant unit is greater than the first capacity threshold, set the output level according to the second rated output ratio;

[0082] For slow-adjusting units, when the unit capacity of the power plant unit is less than the first capacity threshold, set the output level according to the second rated output ratio; when the unit capacity of the power plant unit is greater than the first capacity threshold, set the output level according to the third rated output ratio;

[0083] Among them, the first rated output ratio is less than the second rated output ratio is less than the third rated output ratio.

[0084] For example, the first rated output ratio can be 5%, the second rated output ratio can be 10%, and the third rated output ratio can be 15%.

[0085] In this step, according to the unit capacities of the fast-adjusting units and slow-adjusting units, different rated output ratio is adopted to divide the output levels, and the corresponding rated output ratio relationships under different capacity thresholds are clarified. This division method can give full play to the adjustment capabilities of different types of units, enabling the units to reasonably allocate their outputs at different capacities, and further improving the optimization effect of the unit load carrying capacity.

[0086] Step 104: Optimize the output levels of the power plant units based on the pre-determined health status levels of the power plant units.

[0087] In this step, optimizing the output levels of the power plant units based on the pre-determined health status levels of the power plant units includes:

[0088] When the health status level of the power plant unit is lower than the preset health threshold, reduce the rated output ratio of the output level of the power plant unit;

[0089] When the health status level of the power plant unit is higher than the preset health threshold, increase the rated output ratio of the output level of the power plant unit.

[0090] The size of the preset health threshold can be set as needed and is not specifically limited here.

[0091] Specific example: Suppose a power plant has two units: Unit A and Unit B. Their health status levels are calculated through a pre-established assessment model as follows:

[0092] Unit A: The health status level is 70 (out of 100), lower than the preset health threshold of 80; the rated output ratio of the original output level is 10% (assuming its capacity is greater than the first capacity threshold and is set according to the second rated output ratio); since the health status level of Unit A is lower than the preset health threshold of 80, it is necessary to reduce the rated output ratio of its output level. Suppose it is reduced by 2 percentage points, then the adjusted rated output ratio is 8%.

[0093] Unit B: The health status level is 90, higher than the preset health threshold of 80; the rated output ratio of the original output level is 10% (assuming its capacity is greater than the first capacity threshold and is set according to the second rated output ratio); since the health status level of Unit B is higher than the preset health threshold of 80, the rated output ratio of its output level can be increased. Suppose it is increased by 2 percentage points, then the adjusted rated output ratio is 12%.

[0094] Optimized result: Since Unit A is in poor health, by reducing the rated output ratio of its output gear, the operating load of the unit can be reduced, avoiding unit failures caused by excessive load, thereby extending the service life of the unit and improving operating reliability. Unit B: Since it is in good health, by increasing the rated output ratio of its output gear, its load-carrying capacity can be fully utilized, improving the economy of the unit and ensuring the overall stable operation of the power grid. It can be understood that even after increasing the rated output ratio of its output gear, it is not allowed to exceed the maximum capacity.

[0095] Step 105: Under each operating mode, perform stability check based on the output gear of the power plant unit.

[0096] In this step, performing stability check based on the output gear of the power plant unit includes:

[0097] When the power plant unit is at each output gear, perform thermal stability check, transient voltage stability check, and transient power angle stability check.

[0098] Among them, the thermal stability check includes:

[0099] Under normal mode and fault mode, after newly commissioned power plant units or new loads are added, detect whether the active power transmitted by each substation and line belongs to their respective preset power ranges.

[0100] Specifically, the normal mode can be understood as that the equipment is in the operating state as required. The fault mode can be understood as simulating possible fault conditions in the power grid, such as the withdrawal of equipment such as lines, transformers, and units from operation. Under the normal mode, calculate the active power transmission of each substation and line after newly commissioned units or new loads are added. Under the fault mode, calculate the change in active power transmission of each substation and line after the fault occurs. Check whether the active power of each substation and line is within the preset power range. If the active power exceeds the thermal stability limit, it is necessary to adjust the unit output or limit the load. If the active power of a certain line or substation is out of limit, it is necessary to locate the load station or unit causing the overlimit, and by adjusting the unit output or limiting the active power of the load station, make the system meet the thermal stability constraint.

[0101] The transient voltage stability check includes:

[0102] Judge whether the reduction amplitude of the load bus voltage after the fault meets the preset transient voltage stability constraint; among them, the preset transient voltage stability constraint is that the load bus voltage can recover above the preset threshold (for example, 0.8 p.u.) within the preset duration (for example, 10 s).

[0103] Specifically, perform a fault scan on the system, such as line faults, transformer faults, etc., record the voltage changes of each load bus after the fault occurs, and check whether the voltage of the load bus returns above the preset threshold within the preset duration in seconds. If not satisfied, it is necessary to locate the load station or unit that causes voltage instability. If the voltage of a certain load bus does not meet the transient voltage stability constraint, it is necessary to adjust the output of relevant units or limit the active power of the load station until the constraint conditions are met.

[0104] The transient power angle stability check includes:

[0105] Judge whether the maximum power angle difference during the power angle swing of each power plant unit in the network is less than or equal to the preset angle (e.g., 180°), and whether the power angle swing of each power plant unit shows a trend of decaying oscillation and finally stabilizes within the preset interval range.

[0106] Specifically, record the power angle changes of each unit after the fault occurs, check whether the power angle difference of each unit exceeds the preset angle, and check whether the power angle swing of each unit shows a trend of decaying oscillation. If the power angle of a certain unit does not meet the transient power angle stability constraint, it is necessary to adjust the output of relevant units or limit the active power of the load station until the constraint conditions are met. Show a trend of decaying oscillation and finally stabilize within the preset interval range, that is, tend to be stable.

[0107] This step gives specific check criteria and judgment bases, so as to comprehensively and accurately evaluate the stability of power plant units, provides reliable constraint conditions for optimizing the model, and further ensures the safe and stable operation of the power grid. During the checking process, the above-mentioned calculation boundary conditions can be referred to.

[0108] Step 106: Construct an optimization model with the maximization of the active power of the load station as the objective function.

[0109] In this step, add the active powers of all load stations to form a comprehensive objective function. The goal of the optimization model is to find a unit output allocation scheme that maximizes the total active power of the load stations. Generally, simple programming tools (such as Python) can be used to define the objective function and constraint conditions, call the solver to solve the optimization problem, and then output the optimal solution.

[0110] Specifically, the objective function can be shown as the following formula (1):

[0111]

[0112] Among them, A is the total number of load stations, a represents one of the load stations, and P L (a) is the active power of load station a, and max represents solving the maximum value.

[0113] Step 107: Introduce stability check as a constraint condition for the optimization model.

[0114] In this step, the stability check can refer to Step 105. Generally, the mathematical expressions of each constraint condition can be determined and then added to the optimization model.

[0115] Step 108: Solve the optimization model through an optimization algorithm to obtain the maximum load-carrying capacity of the power plant unit.

[0116] In this step, an appropriate optimization algorithm is selected according to the complexity of the optimization problem. Common optimization algorithms include linear programming (LP), nonlinear programming (NLP), genetic algorithm (GA), particle swarm optimization (PSO), etc. Generally, the initial parameters of the optimization algorithm can be set first, such as the initial output of the unit and the initial power of the load station. Through iterative calculations, the unit output and the load station power are gradually adjusted to find the optimal solution that satisfies the constraint conditions. In each iteration, it is checked whether the thermal stability, transient voltage stability, and transient power angle stability constraints are satisfied. When the objective function value no longer changes significantly and all constraint conditions are met, it is considered that the optimization algorithm converges, and the optimal solution is output, that is, the maximum load-carrying capacity of the power plant unit.

[0117] In this embodiment, by comprehensively considering various constraint conditions of the power grid system, the load-carrying capacity of the unit can be calculated more accurately. It can maximize the load-carrying capacity of the unit on the premise of ensuring the safe and stable operation of the power grid, which helps to better meet the load growth demand, especially in areas with rapid load growth. Through stability checks (such as transient voltage stability, transient power angle stability, etc.), it is ensured that the power grid can maintain stable operation under various operating modes and fault conditions. Improve the power grid's ability to respond to sudden faults and reduce the power outage risk.

[0118] In an embodiment of this specification, the determined health status level of the power plant unit includes:

[0119] Collect the operation data of the power plant unit within a preset time period; among them, the operation data includes the number of startups, the number of shutdowns, the number of faults, and the maintenance records;

[0120] Based on the operation data, use a preset health assessment model to calculate the health status level of the power plant unit.

[0121] In this embodiment, by collecting the operation data of the unit and using the health assessment model to calculate the health status level of the unit, the health condition of the unit can be evaluated more accurately through a quantitative method, making the subsequent optimization and adjustment more targeted and effective. The health assessment model is a data analysis-based tool for evaluating the health status of power plant units. It collects and analyzes the operation data of the unit (such as the number of startups, shutdowns, failures, and maintenance records, etc.), and uses statistical analysis methods or preset evaluation rules to calculate the health status level of the unit.

[0122] In an embodiment of this specification, calculating the health status level of a power plant unit based on the operation data by using a preset health assessment model includes:

[0123] Normalize the operation data;

[0124] Based on statistical analysis methods, establish the correlation between each operation data and the health status of the unit;

[0125] Based on the correlation, determine the health score of each operation data;

[0126] Based on the health scores of each operation data, obtain the health status level of the power plant unit.

[0127] In this embodiment, by normalizing the operation data, establishing the correlation between each operation data and the health status of the unit, determining the health score of each operation data, and finally obtaining the health status level of the unit. This process can more accurately quantify the health condition of the unit, provide a more accurate reference for the optimization and adjustment of the output gear, and improve the reliability of the unit operation.

[0128] In an embodiment of this specification, the establishing the correlation between each operation data and the health status of the unit based on statistical analysis methods includes:

[0129] Collect the historical operation data of the unit and its corresponding health status level as sample data;

[0130] Adopt statistical analysis methods such as Pearson correlation coefficient or Spearman rank correlation coefficient to calculate the correlation between each operation data and the health status level of the unit;

[0131] According to the correlation results, determine the influence weight of each operation data on the health status of the unit.

[0132] In this embodiment, the specific steps of establishing the correlation between each operation data and the unit health status by using the statistical analysis method are clarified. By collecting historical sample data, calculating the correlation by using methods such as the Pearson correlation coefficient or the Spearman rank correlation coefficient, and determining the influence weight of each operation data on the unit health status, a scientific and reasonable basis is provided for the subsequent calculation of the health score, enhancing the accuracy and reliability of the health status level assessment.

[0133] In an embodiment of this specification, determining the health score of each operation data based on the correlation includes:

[0134] According to the influence weight of each operation data on the unit health status, perform weighted summation on the normalized operation data to obtain the health score of each operation data, as shown in the following formula (2):

[0135] where S is the health score of all operation data, w i is the influence weight of the i-th type of operation data, x i is the i-th normalized operation data, and n is the number of types of operation data.

[0136] In this embodiment, by performing weighted summation on the normalized operation data according to the influence weight of each operation data, the contribution degree of each operation data to the unit health status can be more accurately reflected, further improving the accuracy of the health status level assessment and providing a more reliable health status basis for the optimization of the output gear position.

[0137] In an embodiment of this specification, obtaining the health status level of the power plant unit based on the health scores of each operation data includes:

[0138] Calculate the comprehensive health score of the unit by calculating the health scores of each operation data based on weighted average or non-linear combination function;

[0139] According to the preset health status level division standard, map the comprehensive health score to the corresponding health status level.

[0140] In this embodiment, calculate the comprehensive health score of the unit by using weighted average or non-linear combination function to calculate the health scores of each operation data, and map the comprehensive health score to the corresponding health status level according to the preset standard. This makes the assessment of the unit health status more comprehensive and systematic, provides more scientific and accurate health status information for the subsequent optimization adjustment of the output gear position, and helps to efficiently improve the unit load carrying capacity.

[0141] In some other embodiments of this specification, before normalizing the operation data, it may further include:

[0142] Based on the timestamps of the operation data, the operation data is divided into multiple data groups according to time intervals;

[0143] Then, the following steps are performed for each data group:

[0144] Perform normalization processing on the operation data;

[0145] Collect historical unit operation data and its corresponding health status levels as sample data;

[0146] Adopt statistical analysis methods such as Pearson correlation coefficient or Spearman rank correlation coefficient to calculate the correlation between each operation data and the unit health status level;

[0147] According to the correlation results, determine the influence weights of each operation data on the unit health status;

[0148] According to the influence weights of each operation data on the unit health status, perform weighted summation on the normalized operation data to obtain the health scores of each operation data.

[0149] Then, sum up the health scores of each data group to obtain the final health score. Specifically, it is shown in the following formula (3):

[0150]

[0151] Among them, S is the health score of all operation data, n is the number of types of operation data, m is the number of data groups, w ij is the influence weight of the i-th type of operation data in the j-th data group, and x ij is the normalized value of the i-th type of operation data in the j-th data group.

[0152] In this embodiment, by grouping the unit operation data by time, the refined management of the unit operation state is realized, the accuracy of the unit health status assessment is improved, and it is made more in line with the actual operation situation.

[0153] In some other embodiments of this specification, the method for improving the unit load carrying capacity further includes:

[0154] Introduce environmental factor constraints into the optimization model, and the environmental factor constraints include carbon emission constraints and renewable energy utilization rate constraints.

[0155] The carbon emission constraint is: on the premise of meeting the load demand, limit the carbon emission per unit time during the operation of the power plant unit not to exceed a preset threshold;

[0156] The renewable energy utilization rate constraint is: ensure that the proportion of the power generation of renewable energy in the power grid system in the total power generation is not less than a preset proportion.

[0157] In this embodiment, by introducing environmental factor constraints, while improving the load carrying capacity of the unit, environmental protection and sustainable development can be taken into account, making the power grid operation more green and low-carbon.

[0158] In some other embodiments of this specification, the method for improving the load carrying capacity of the unit further includes:

[0159] When determining the output gear of the power plant unit, an environmental adaptability evaluation module is introduced;

[0160] The environmental adaptability evaluation module dynamically adjusts the output gear of the unit according to the climate conditions (such as temperature, humidity, wind speed), geographical conditions (such as altitude, topography) and seasonal changes in the area where the power grid is located;

[0161] For example, in an environment where the temperature is higher than the first preset temperature or the humidity is higher than the preset humidity, the output gear of the unit is appropriately reduced to reduce the thermal stress and cooling requirements of the unit; during low load in winter (when the temperature is lower than the second preset temperature), the output gear of the unit is appropriately increased to make full use of the power generation capacity of the unit; the second preset temperature is lower than the first preset temperature;

[0162] In this embodiment, through the dynamic adjustment of the environmental adaptability evaluation module, it is ensured that the unit can operate efficiently under different environmental conditions and the load carrying capacity is improved.

[0163] To facilitate a clearer understanding of the present invention, the solution of the present invention will be introduced as a whole below.

[0164] Detect information such as the voltage of each node and the line power flow in the system before and after the unit is connected to the power grid. After the unit is put into operation, first, under each operation mode and each unit starting level, it is classified according to the unit output classification method proposed by the present invention.

[0165] Then, a security and stability check is carried out under each unit classification. First, a thermal stability constraint check is carried out, that is, under normal mode and maintenance mode, the whole network lines and substations are scanned and the power flow section analysis after each opening is carried out one by one. The fluctuation values of the power flow power of each substation and each line in the research area are detected, and it is judged whether the thermal stability requirements are met through inequality constraints. If it is met and the margin is large, the load of the load station can be continuously increased until the power flow of the substation and the line both meet the static security constraint critical requirements; if it is not met, it is necessary to locate which load station's active power causes the node voltage or line power flow to exceed the limit, that is, find the load station with the largest influence factor, and then limit the active power of this load station until the power flow of the substation or the line both meet the thermal stability constraint critical requirements.

[0166] Perform transient stability verification. Conduct various large disturbance fault scans on the system, and monitor the node voltages of each load bus and the power angles of each unit. If during the transient process after being disturbed, the load bus voltages can all meet the requirement of recovering above 0.8 p.u. within 10 s, and the power angle stability requirements of each unit are met with a large margin, then the active power of the load station can be continuously increased until the voltage at the load bus meets the critical constraints of transient voltage and transient power angle. If not, it is necessary to locate which load stations' active powers do not meet the requirements or the power angles are unstable, and then limit the active power of the load station until the voltage at the load bus meets the critical constraints of transient voltage and transient power angle.

[0167] Specifically, the transient voltage stability constraint formula is as shown in formula (4) below:

[0168]

[0169] Among them, V k，t (t) represents the voltage value of node k at time t; V crit is the limit value of voltage reduction, that is, the maximum value by which the voltage can be reduced; f ∈ N is node f in the node set N; t ∈ [t1, t2] represents the time interval from t1 to t2; T crit represents the time threshold, that is, the maximum allowable time for the voltage to recover above the limit value; V k，f (t) represents the voltage amplitude of node k under the condition of fault f at time t.

[0170] The transient power angle stability constraint is as shown in formula (5) below:

[0171] |δ k,p (t) - δ k,q (t)| ≤ δ max , (5);

[0172] Among them, p ≠ q, p ∈ G, q ∈ G, k ∈ C, t ∈ [0, T], t represents time, T is the time period of the transient process under study; δ max is the allowable upper limit value of power angle swing; δ k,p (t) and δ k,q (t) are the power angles of any two units under the fault condition; G and C respectively represent the set of generators in the system and the set of contingency faults.

[0173] The following will elaborate on the present invention through specific examples. Figure 2 is a schematic diagram of the grid architecture of a region provided by an embodiment of the present invention. Refer to Figure 2, 500kV BL: 500 kV substation, BL represents the number of the substation. 220kVWS: 220 kV substation, WS represents the number of the substation. 220kVXH: 220 kV substation, XH represents the number of the substation. 500kV DL: 500 kV substation, DL represents the number of the substation. 500kVCKS: 500 kV substation, CKS represents the number of the substation. 500kV BT: 500 kV substation, BT represents the number of the substation. 220kVLW: 220 kV substation, LW represents the number of the substation. 220kV LL: 220 kV substation, LL represents the number of the substation. 500kV WC: 500 kV substation, WC represents the number of the substation. 220kVGY power plant: 220 kilovolt power plant, GY represents the power plant number. 220kVHY power plant: 220 kilovolt power plant, HY represents the power plant number.

[0174] (1) A 220kV HY power plant in a certain power grid is located at the end of the power grid. According to the grid planning, the power plant will put into operation the third unit with a capacity of 1×350MW. At that time, the grid structure of the power grid in the area will be as follows: Figure 2 Among them, GY power plant is directly connected to the 220kV side of 500kVCKS substation through double-circuit 220kV lines, HY power plant is connected to LW load station through double-circuit 220kV lines, and LW load station is connected to the 220kV side of 500kVCKS substation through double-circuit 220kV lines.

[0175] (2) Safety and stability verification: After the third unit of HY Power Plant was put into operation, the unit was graded according to the unit grading method proposed in the present invention, and the voltage of the 500kV CKS main transformer was controlled to be around 515kV. In normal and maintenance modes, various lines and main transformer N-1 faults in the area were verified, and the transient stability of the area was verified. The load-bearing capacity of the unit after commissioning was determined. Taking the normal mode as an example, the calculation results are shown in Table 1 below, indicating that 1 can represent the load calculation limit of LW station + LL station under different outputs of HY Power Plant.

[0176] Table 1

[0177]

[0178] (3) As shown in Table 1, by controlling the output of the HY power plant units in different stages, the regional load-carrying capacity gradually increases, which is inversely proportional to the unit output. The change trend is shown in the figure below: Figure 3 and Figure 4 As shown, the simulation results demonstrate the effectiveness of the method proposed in the present invention.

[0179] In some other embodiments of this specification, the method further includes:

[0180] Introduce the start-stop cost constraint into the optimization model. The start-stop cost constraint is that, on the premise of meeting the load demand, the total cost of restricting the start-stop operation of the units does not exceed the preset cost threshold. The start-stop cost includes the unit start-up cost, shutdown cost, and equipment loss cost caused by the start-stop operation.

[0181] According to the type, capacity, and health status level of the units, dynamically calculate the start-stop cost weights of each unit and incorporate them into the objective function of the optimization model. Through the optimization algorithm, comprehensively consider the load-carrying capacity and start-stop cost to obtain the optimal unit output allocation plan.

[0182] In some other embodiments of this specification, the method further includes:

[0183] Introduce the distributed energy access constraint into the optimization model. The distributed energy access constraint is that, on the premise of meeting the load demand, the maximum capacity ratio of distributed energy (such as solar energy, wind energy, energy storage systems, etc.) accessing the power grid is restricted.

[0184] According to the output characteristics, access location, and grid consumption capacity of the distributed energy, dynamically adjust the access capacity of the distributed energy and incorporate it into the constraint conditions of the optimization model.

[0185] Through the optimization algorithm, coordinate the unit output and the access of distributed energy to achieve the multi-energy complementarity of the power grid and the improvement of the load-carrying capacity, while ensuring the safe and stable operation of the power grid.

[0186] Specifically, according to the output characteristics, access location, and grid consumption capacity of the distributed energy, dynamically adjust the access capacity of the distributed energy and incorporate it into the constraint conditions of the optimization model, including:

[0187] (1) Analysis of distributed energy output characteristics:

[0188] Collect the historical output data of the distributed energy, including the output curves of solar energy, wind energy, and energy storage systems.

[0189] Analyze the output fluctuation characteristics of the distributed energy to determine its output fluctuation range and probability distribution.

[0190] Based on the output fluctuation characteristics, calculate the available output range of the distributed energy, that is, the reliable output values within different time scales (such as hours, days).

[0191] (2) Evaluation of access location and consumption capacity:

[0192] Determine the access points of the distributed energy, including the specific substations or lines to be accessed.

[0193] Analyze the power grid topology structure and power flow distribution of the access point, and evaluate the accommodation capacity of the access point, including line capacity, substation capacity, and load demand;

[0194] Based on the accommodation capacity, determine the maximum access capacity limit of distributed energy to ensure that the grid will not be overloaded or the voltage will not exceed the limit after access.

[0195] (3) Dynamically adjust the access capacity:

[0196] Dynamically adjust the access capacity of distributed energy according to the available output range of distributed energy and the accommodation capacity of the access point;

[0197] During the peak load period of the power grid, give priority to using the available output of distributed energy to reduce the output demand of the units;

[0198] During the low load period of the power grid, adjust the charge and discharge power of the energy storage system according to the state of the energy storage system to optimize the access capacity of distributed energy.

[0199] (4) Incorporate constraint conditions into the optimization model:

[0200] Take the access capacity limit of distributed energy as a constraint condition of the optimization model to ensure that the access of distributed energy during the optimization process does not violate the requirements for the safe operation of the power grid;

[0201] Introduce a penalty factor for the output fluctuation of distributed energy in the optimization model to give appropriate penalties to the cases where the output of distributed energy fluctuates greatly, so as to improve the stability of the power grid operation.

[0202] Coordinate the output of the units and the access of distributed energy through an optimization algorithm to achieve multi-energy complementarity of the power grid and improve the load-carrying capacity, while ensuring the safe and stable operation of the power grid, including:

[0203] (1) Construction of the multi-energy complementarity optimization objective:

[0204] In the optimization model, take the output of the units and the output of distributed energy as optimization variables to construct an objective function for multi-energy complementarity;

[0205] The objective function includes two parts: maximizing the active power of the load station and minimizing the start-stop cost of the units, while considering the access cost and output fluctuation penalty of distributed energy;

[0206] Combine the above objective functions into a comprehensive optimization objective by weighted summation.

[0207] (2) Selection of the optimization algorithm and parameter setting:

[0208] Select an algorithm suitable for multi-energy complementarity optimization, such as genetic algorithm, particle swarm optimization algorithm, or mixed integer linear programming algorithm;

[0209] Set the parameters of the optimization algorithm, such as population size, number of iterations, crossover probability, and mutation probability, according to the scale of the power grid and the complexity of the optimization problem.

[0210] (3) Implementation of the optimization process:

[0211] Initialize the initial values of the unit output and the access capacity of distributed energy resources;

[0212] Run the optimization algorithm, gradually adjust the unit output and the access capacity of distributed energy resources, and find the optimal solution that meets the constraint conditions;

[0213] In each iteration, check whether the optimization result meets the constraints of the power grid's thermal stability, transient voltage stability, and transient power angle stability;

[0214] If the constraint conditions are not met, adjust the optimization variables and re-perform the optimization calculation.

[0215] (4) Verification and adjustment of the optimization result:

[0216] Verify the effectiveness of the optimization result, including whether the unit output and the access capacity of distributed energy resources meet the requirements for the safe operation of the power grid;

[0217] If the optimization result is not ideal or there are potential risks, adjust the parameters or constraint conditions of the optimization model according to the actual situation and re-perform the optimization calculation;

[0218] Output the final optimization result, including the unit output allocation plan and the access capacity plan of distributed energy resources, for guiding the actual operation of the power grid.

[0219] In some other embodiments of this specification, the improvement method further includes:

[0220] Based on the dynamic adjustment mechanism of the unit health status level, the health status level of the unit is updated in real time.

[0221] Specifically, by real-time monitoring of the unit's operation data (including but not limited to the number of starts, stops, faults, and maintenance records), combined with a preset health assessment model, the health status level of the unit is dynamically calculated.

[0222] When the health status level of the unit changes, the re-optimization of the output gear is automatically triggered to ensure that the unit can still maintain the optimal load-carrying capacity when the health status changes.

[0223] Based on the same general inventive concept, the present invention also protects a system for improving the load-carrying capacity of a unit, as Figure 5 shown, Figure 5It is a schematic structural diagram of a system for improving the unit load acceptance capacity provided by an embodiment of the present invention. The system for improving the unit load acceptance capacity provided by the present invention will be described below. The system for improving the unit load acceptance capacity described below can be mutually corresponding and referred to the method for improving the unit load acceptance capacity described above.

[0224] The system for improving the unit load acceptance capacity includes a boundary determination module 201, a unit division module 202, a gear division module 203, a gear optimization module 204, a stability verification module 205, a model establishment module 206, a constraint introduction module 207, and a load calculation module 208.

[0225] The boundary determination module 201 is used to determine the calculation boundary conditions of the power grid system within a preset area and the operation modes of the power plant units based on the power grid system information;

[0226] The unit division module 202 is used to divide the power plant units into fast-adjusting units and slow-adjusting units based on the adjustment time of the power plant units;

[0227] The gear division module 203 is used to divide the output gears of the power plant units based on the unit capacities of the fast-adjusting units and the slow-adjusting units;

[0228] The gear optimization module 204 is used to optimize the output gears of the power plant units based on the pre-determined health status levels of the power plant units;

[0229] The stability verification module 205 is used to perform stability verification based on the output gears of the power plant units under each of the operation modes;

[0230] The model establishment module 206 is used to construct an optimization model with the maximization of the active power of the load station as the objective function;

[0231] The constraint introduction module 207 is used to introduce the stability verification as a constraint condition of the optimization model;

[0232] The load calculation module 208 is used to solve the optimization model through an optimization algorithm to obtain the maximum value of the load carried by the power plant units.

[0233] Figure 6 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. As Figure 6As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communication bus 340. Among them, the processor 310, the communications interface 320, and the memory 330 communicate with each other through the communication bus 340. The processor 310 can call the logical instructions in the memory 330 to execute the method for improving the unit load carrying capacity.

[0234] In addition, when the logical instructions in the above-mentioned memory 330 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0235] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for improving the unit load carrying capacity provided by the above-mentioned various methods.

[0236] On yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the method for improving the unit load carrying capacity provided by the above-mentioned various methods.

[0237] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0238] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0239] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for improving the load carrying capacity of a unit, characterized in that: include: Based on the grid system information, determine the calculation boundary conditions of the grid system and the operation mode of the power plant units in the preset area; Based on the regulation time of power plant units, power plant units are divided into fast regulation units and slow regulation units; Based on the unit capacities of the fast-adjusting units and the slow-adjusting units, dividing the output gears of the power plant units; Optimize the output gear of the power plant units based on the pre-determined health status level of the power plant units; Under each of the operating modes, stability verification is performed based on the output gear of the power plant unit; Construct an optimization model with load station active power maximization as the objective function; Introducing the stability check as a constraint condition of the optimization model; The optimization model is solved by an optimization algorithm to obtain the maximum value of the load carried by the power plant units.

2. The method for improving the load carrying capacity of a unit according to claim 1, characterized in that: The stability check based on the output gear of the power plant unit includes: When the power plant units are in various output gears, thermal stability checks, transient voltage stability checks and transient power angle stability checks are performed; wherein, The thermal stability check comprises: In normal mode and fault mode, after the new power plant units are put into operation or the new loads are added, the active power transmitted by each substation and line is detected to see whether it falls within the respective preset power range; The transient voltage stability check includes: Determine whether the reduction range of the load bus voltage after the fault meets the preset transient voltage stability constraint; wherein the preset transient voltage stability constraint is that the load bus voltage can be restored to above the preset threshold within a preset time; The transient power angle stability check includes: Determine whether the maximum power angle difference during the power angle swing of each power plant unit in the grid is less than or equal to the preset angle, and whether the power angle swing of each power plant unit shows a trend of attenuated oscillation, and finally stabilizes within the preset range.

3. The method for improving the load carrying capacity of a unit according to claim 1, characterized in that: The calculation boundary conditions include the maximum operating capacity, load power factor and bus voltage of the substation, and the operation mode includes the startup combination mode of the power plant units and the maintenance mode of the power grid system; wherein, The maximum operating capacity of the substation is determined by: Based on the rated capacity and historical operating capacity data of the substation in the preset area, the maximum operating capacity of the substation is obtained; The load power factor is determined by: Analyze the load power factor variation pattern in the preset area and determine the value range of the load power factor; The bus voltage is determined by: Based on the operating voltage curve of the bus, the voltage fluctuation range in the historical data is extracted, and the lower limit value of the operating voltage curve is combined with the lowest point of the voltage fluctuation to determine the bus voltage; The startup combination mode includes starting all power plant units at the same time and starting some power plant units at the same time; The maintenance method includes a single exit maintenance method for adjacent lines, units, and transformers.

4. The method for improving the load carrying capacity of a unit according to claim 1, characterized in that: The step of dividing the output gears of the power plant units based on the unit capacities of the fast-adjusting units and the slow-adjusting units includes: For the fast adjustment unit, when the unit capacity of the power plant unit is less than the first capacity threshold, the output gear is set according to the first rated output ratio; when the unit capacity of the power plant unit is greater than the first capacity threshold, the output gear is set according to the second rated output ratio; For the slow-speed regulating unit, when the unit capacity of the power plant unit is less than the first capacity threshold, the output gear is set according to the second rated output ratio; when the unit capacity of the power plant unit is greater than the first capacity threshold, the output gear is set according to the third rated output ratio; Among them, the first rated output ratio is smaller than the second rated output ratio, which is smaller than the third rated output ratio.

5. The method for improving the load carrying capacity of a unit according to claim 4, characterized in that: The step of optimizing the output gear of the power plant unit based on the predetermined health status level of the power plant unit comprises: When the health status level of the power plant unit is lower than the preset health threshold, the rated output ratio of the output gear of the power plant unit is reduced; When the health status level of the power plant unit is higher than the preset health threshold, the rated output ratio of the output gear of the power plant unit is increased.

6. The method for improving the load carrying capacity of a unit according to claim 5, characterized in that: The determined health status level of the power plant unit includes: Collecting the operating data of the power plant units within a preset time period; wherein the operating data includes the number of starts, the number of shutdowns, the number of failures and maintenance records; Based on the operating data, a preset health assessment model is used to calculate the health status level of the power plant unit.

7. The method for improving the load carrying capacity of a unit according to claim 6, characterized in that: The step of calculating the health status level of the power plant unit based on the operation data using a preset health assessment model includes: performing normalization processing on the operation data; Based on statistical analysis methods, the correlation between various operating data and the health status of the unit is established; Based on the correlation, determine the health score of each operating data; Based on the health scores of various operating data, the health status level of the power plant units is obtained.

8. The method for improving the load carrying capacity of a unit according to claim 7, characterized in that: The statistical analysis method is used to establish the correlation between the operating data and the health status of the unit, including: Collect historical unit operation data and its corresponding health status level as sample data; Statistical analysis methods such as Pearson correlation coefficient or Spearman rank correlation coefficient are used to calculate the correlation between various operating data and the unit health status level; According to the correlation results, determine the impact weight of each operating data on the health status of the unit.

9. The method for improving the load carrying capacity of a unit according to claim 8, characterized in that: The health score of each operation data is determined based on the correlation, including: According to the influence weight of each operating data and the health status of the unit, the normalized operating data is weighted and summed to obtain the health score of each operating data. The formula is as follows: Among them, S is the health score of all running data, w i is the influence weight of the i-th running data, x i is the normalized operating data of the ith type, and n is the number of types of operating data.

10. The method for improving the load carrying capacity of a unit according to claim 8, characterized in that: The health score based on each operation data is used to obtain the health status level of the power plant unit, including: The health score of each operating data is calculated based on the weighted average or nonlinear combination function to obtain the comprehensive health score of the unit; According to the preset health status level classification standards, the comprehensive health score is mapped to the corresponding health status level.

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